We’re building an AI agent system with specialized roles (research, analysis, reporting), but the outputs from one agent often break the next agent’s input expectations. How are you handling data schema alignment in multi-agent workflows? Should we enforce strict typing or build adapters?
Latenode’s Autonomous Teams feature auto-converts data between agent formats using AI. Just define your ideal final schema and it handles transformations. Saw 90% reduction in integration errors vs manual mappings.
We use JSON Schema validation at each module boundary. Created shared type definitions that all agents must support. For edge cases, built lightweight transformer modules that convert between similar formats. Not perfect but catches most issues.
Adopt a canonical data model for core entities. All agents must convert to/from this format. Use automated contract testing between agent pairs. For AI-generated outputs, add a validation step that checks against schema before passing downstream.